Ultra-Fast Whole-Body Bone Tomoscintigraphies Achieved With a High-Sensitivity 360° CZT Camera and a Dedicated Deep Learning Noise Reduction Algorithm
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 19
- 试验地点
- 1
- 主要终点
- Assess a dedicated deep learning noise reduction algorithm
研究概览
简要总结
This study aimed to determine whether the whole-body bone Single Photon Emission Computed Tomography (SPECT) recording times of around 10 minutes, routinely provided by a high-sensitivity 360 degrees cadmium and zinc telluride (CZT) camera, can be further reduced by a deep learning noise reduction (DLNR) algorithm.
详细描述
This study aimed to determine the extent to which fast whole-body bone-SPECT recording times, routinely obtained with a high-sensitivity 360 degrees CZT-camera and rather low injected activities, can be further reduced using the DLNR algorithm.
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 95 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •patients referred to fast whole-body bone single photon emission tomography for detection or follow-up of bone metastasis
排除标准
- 未提供
结局指标
主要结局
Assess a dedicated deep learning noise reduction algorithm
时间窗: one day
A deep learning noise reduction algorithm was applied on whole-body images recorded
次要结局
未报告次要终点
研究者
Achraf BAHLOUL
Principal investigator
Central Hospital, Nancy, France